Key Responsibilities

Diagnose and resolve complex technical issues across OpenRouter's API, spanning multiple LLM providers
Reproduce bugs in ambiguous environments — different SDKs, languages, frameworks, and auth configurations — using tools like curl, Postman, and small test apps
Read and interpret logs, headers, and request traces; identify whether the problem is client-side, OpenRouter-side, or an upstream provider issue vs. a user misconfiguration
Turn "it doesn't work" into actionable findings: exact steps to reproduce, clear hypotheses, and verified fixes or workarounds

Respond to developer inquiries across support channels (email, Discord, GitHub) with clarity, empathy, and technical precision
Translate complex technical root causes into human-friendly explanations
Set expectations on timelines and next steps; provide proactive updates and close the loop
Identify patterns in support requests and advocate internally for documentation improvements, API design changes, or better messages

Stay current with the rapidly evolving LLM ecosystem
Develop deep expertise in OpenRouter's routing logic, fallback behavior, rate limiting, streaming (SSE), and billing systems with minimal hand-holding

Spot systemic issues underneath individual tickets and push for the fix that prevents 50 more
Identify trends in support volume to capture product feedback and inform roadmap priorities
Collaborate on improving the developer experience

Requirements

4+ years in a technical support, developer support, solutions engineering, or similar role — ideally supporting an API or developer tools product
Exceptional troubleshooting instincts
Strong API fluency
Proficiency in at least one scripting language (Python or TypeScript)
Excellent written communication
Comfort with ambiguity
Genuine passion for AI and LLMs

Familiarity with the OpenAI SDK / Chat Completions API format
Experience with AI/ML frameworks like LangChain, LlamaIndex, or Hugging Face
Experience with observability tools (logging, tracing, metrics)
Experience scaling support operations — e.g., implementing AI-assisted support bots, building internal support dashboards, or creating automated triage workflows
Contributions to open-source projects or developer communities
Background in or exposure to ML/AI concepts beyond just using APIs (benchmarking, evals, fine-tuning)